Microsoft has quietly added a low‑latency profile to Windows 11 that momentarily raises CPU frequency for high‑priority UI tasks, and tests on low‑end hardware show up to a 70% reduction in menu‑click lag and up to 40% faster app launches with minimal impact on battery life or thermals.
This article explains how Linux memory watermarks, kswapd, direct reclaim, and the OOM Killer interact, provides detailed code examples, shows real‑world case studies, and offers practical tuning steps—including kernel parameters, cgroup limits, and monitoring tools—to prevent system stalls and crashes.
This article provides a comprehensive framework for evaluating system support capability by defining QPS excellence thresholds across industry benchmarks, business types, response time, resource efficiency, performance metrics, architectural guidelines, optimization tactics, and real‑world case studies, culminating in a practical calculation formula.
This article recounts a two‑week Linux system tuning project that reduced a high‑traffic API’s P99 response time from over 500 ms to under 100 ms by systematically diagnosing bottlenecks, applying USE‑based analysis, and tuning kernel, network, file‑descriptor, memory, CPU, and I/O parameters.
This article explains the key performance metrics TPS (transactions per second) and QPS (queries per second), provides formulas for calculating them, and demonstrates practical calculations for multi-node deployments, illustrating how request latency, thread pools, and instance count affect overall system concurrency and throughput.
On Linux and macOS, the article compares the classic top command with its more user‑friendly alternatives htop and btop, explains installation (brew for macOS), walks through btop’s interface, presets, modules, shortcuts, theming, and shows how to use it for detailed CPU, memory, storage, network, and process monitoring.
This guide uses a four‑detective metaphor to teach Linux process monitoring tools—ps, dstat, top, and htop—covering their options, output fields, interactive commands, and practical examples for effective system performance analysis.
The article examines Linux kernel 6.9 memory-management locks—PG_locked, lru_lock, mmap_lock, anon_vma rwsem, mapping i_mmap_rwsem, and shrinker_rwsem—explaining their roles and presenting eight community-driven optimizations such as per-memcg lru_lock, per-VMA locks, speculative faults, and lock-less shrinker techniques to improve concurrency and performance.
This article explains how to design a comprehensive monitoring system using the concise USE (Utilization, Saturation, Errors) method, outlines essential system and application metrics, and demonstrates practical implementation with Prometheus, Grafana, and related open‑source tools.
This article details the end‑to‑end design, node‑level splitting, metric definition, and Spring‑based implementation of SLA monitoring for a high‑volume message‑push system, showing how precise latency and vendor‑stability metrics uncovered bottlenecks, enabled rapid issue detection, and ultimately doubled overall throughput.
Load balancing, essential for distributed systems and microservices, boosts performance, ensures high availability, provides scalability, improves user experience, and adds security layers, making it a critical technique for modern architecture.
This guide walks you through checking CPU usage, system load, resource consumption, process tracing, log inspection, and performance bottleneck analysis on Linux to pinpoint and resolve high CPU utilization issues.
This guide outlines twelve practical methods—including /proc/meminfo, atop, free, GNOME System Monitor, htop, and others—to help Linux users comprehensively track physical memory, swap, buffers, and cache for performance optimization.
The article explains how the Linux ss command provides comprehensive socket statistics, lists its most useful options, demonstrates performance advantages over netstat with timing examples, and shows how to filter by state, address, or port for efficient system monitoring.
Linus Torvalds, after previously praising AMD, now denounces the AMD fTPM implementation for causing intermittent system hangs on Windows and Linux, explaining the underlying memory‑transaction issue, AMD’s delayed fixes, and his recommendation to disable fTPM in favor of the CPU’s rdrand instruction.
Memory compression techniques like Linux's zSwap, zRAM, and the zstd algorithm reduce I/O latency and extend RAM capacity by compressing swap pages, offering performance gains while introducing trade‑offs such as CPU overhead and configuration complexity, and this guide explains their principles, advantages, drawbacks, and activation steps.
Xiaohongshu transformed its recommendation, advertising, and search inference pipeline by migrating to GPU‑centric hardware, deploying a custom TensorFlow‑Core Lambda service, and applying system‑level, virtualization, and compute‑level optimizations—including NUMA binding, kernel fusion, dynamic scaling, and FP16 quantization—achieving roughly 30× compute capacity growth, over 10% user‑metric gains, and more than 50% cluster‑resource savings.
This article explains Linux load average, covering how it is calculated, its relationship with CPU usage, and how the kernel exposes load data to applications.
This article explains how to build a comprehensive monitoring system using the concise USE (Utilization, Saturation, Errors) method, outlines key system and application metrics, and demonstrates practical implementation with Prometheus, Grafana, full‑link tracing, and ELK for observability and performance troubleshooting.
The article uses thermodynamic analogies to argue that without continuous system optimization teams face entropy, then outlines how managers can find a leverage point, avoid cognitive biases, and adopt three concrete performance metrics—startup time, transaction latency, and issue‑resolution quality—while establishing daily technical‑management habits.
The article explains how R&D managers can boost efficiency by treating team workflows like system performance optimization, using measurement, architectural redesign, and value‑stream analysis to identify bottlenecks and achieve cost‑effective improvements across development, testing, and operations.
This article explains the difference between CPU load and CPU usage, then shows step‑by‑step how to calculate CPU utilization on Linux using vmstat, parsing /proc/stat, and extracting idle percentages from top, with ready‑to‑run command examples for both single‑core and multi‑core systems.
This guide explains how to use Linux’s top command to monitor system performance in real time, covering its statistical and process sections, key fields, useful command‑line options, common interactive operations, and the significance of CPU steal time for virtualized environments.
The article explains how quantifying and measuring both technical systems and organizational processes can reveal inefficiencies, using a concrete image‑processing service example to illustrate how workflow analysis, metric collection, and architectural redesign lead to resource savings and how the same principles apply to DevOps and R&D management.
This guide explains how to use the Linux top command to monitor real‑time process activity, interpret CPU, memory and swap statistics, customize displayed columns, apply command‑line options, and understand key metrics such as load average and steal time for effective system performance management.
The article explains Linux kernel CPU‑time accounting modules—cputime, cpufreq_stats, cpufreq_times, and cpuidle_time—detailing how each records processor usage, frequency transitions, per‑process frequency data, and idle‑state durations, and why they are essential for performance analysis and power‑optimization by system engineers.
The article reports on recent Chinese tech news—from massive travel‑card queries and ByteDance layoffs to Douyin’s remote‑work policy and a new partnership between Taobao and QQ Music—while spotlighting BC‑Linux V8.2, a CentOS‑compatible OS with dual kernels, performance boosts, and enhanced security.
This guide shows how to download, extract, and run the lightweight nmon performance monitoring tool on CentOS 7, including the exact commands to fetch the package, choose the correct binary, start the utility, and view CPU and memory statistics using interactive keys.
The article reviews JD.com’s 11.11 shopping festival technical preparation, detailing how the operations team handled record traffic spikes, improved user experience, increased resource efficiency, and reduced IT costs through high‑fidelity testing, dual‑active systems, and a four‑year Taishan project.
This guide enumerates the key Linux system metrics—covering CPU, memory, disk, I/O, network, kernel parameters, RAID, SMART, NTP, and process information—that open-falcon agents collect every minute to enable comprehensive operations monitoring and timely issue detection.
bashtop is an open-source Linux resource monitor that visualizes CPU, memory, disk, network, and process usage in real time, offering an intuitive, fast-responsive interface with features like process selection, signal sending, filtering, theming, and extensive configuration via a .theme file.
Pressure Stall Information (PSI) is a Linux kernel feature that measures real‑time CPU, memory, and I/O pressure by tracking task wait times, offering finer granularity than load average or vmpressure, and enabling more accurate scheduling, cgroup management, and out‑of‑memory handling.
A user reported extremely slow first SSH login on a UCloud “High‑Kernel Ubuntu 18.04” instance, which was traced to slow entropy‑pool initialization in the Linux kernel, a libssl 1.1.1 bug, and a kernel configuration issue, leading to a fix involving disabling MOTD or enabling CONFIG_RANDOM_TRUST_CPU.
This article systematically explains cache fundamentals, why caching is essential for performance, where caches can be placed in the architecture, their advantages, when to adopt them, and key design considerations for building reliable, high‑throughput systems.
This article explains why a Linux system can show a high load average while CPU utilization remains low, covering the concepts of load, multi‑tasking operating systems, process states, scheduling, and common scenarios that cause I/O‑bound load spikes.
After a decade of using Ubuntu, the author migrated to Manjaro because it feels faster, runs fewer background services, offers a rolling‑release model, and provides a cleaner, more flexible package management system, making the overall Linux experience more efficient and enjoyable.
High system load can occur even when CPU usage is low, typically due to many processes waiting for disk I/O; this article explains load concepts, process states, scheduling, and common scenarios such as excessive I/O requests, unindexed MySQL queries, and faulty external storage that cause such bottlenecks.
This article explains the Linux load average metric, the run queue structure, why both running (R) and uninterruptible (D) processes are counted, and how the kernel uses an exponential weighted moving average to compute the 1‑, 5‑, and 15‑minute load values.
This article consolidates practical knowledge on system performance optimization, covering key metrics, load‑testing utilities, Linux monitoring commands, and JVM profiling tricks to help engineers pinpoint and resolve throughput, latency, CPU, disk, and network bottlenecks.
This article shares real‑world ops stories about a disputed memory upgrade, explains how Linux calculates usable memory, clarifies common subnet‑mask misunderstandings, and demonstrates why Telnet cannot test UDP ports, highlighting practical troubleshooting lessons for system administrators.
The article explains how Unix-like systems calculate load average using an exponentially damped weighted moving average, how the values reflect CPU and I/O contention on single- and multi‑CPU machines, and why different kernel implementations may count processes and threads differently, affecting performance monitoring.
Learn how to install, configure, and use dstat—a versatile, Python‑based Linux monitoring tool that replaces vmstat, iostat, netstat, and more—covering its features, command‑line options, plugins, CSV export, and real‑time performance insights for effective system administration.
